Your agentic enterprise: The new reality of AI and enterprise content

Enterprise leaders are under immense pressure to deliver a return on their AI investments. Organizations have poured nearly $40 billion into generative AI, yet according to MIT’s State of AI in Business, 2025, a staggering 95% of these pilots fail to deliver measurable ROI.

This widespread failure has created a data-rich, intelligence-poor environment where the promise of AI remains just out of reach.

That trend line must change for you to harness the full power and potential of AI at your enterprise.

Hyland has a roadmap — and the technology in place — to help you do just that. In this article, let’s explore how you can:

• Break through the debilitating fragmentation that keeps your enterprise content in a state of chaos

• Start unifying your content and data, so you’re feeding your AI solutions optimal inputs

• Capitalize on the context and insight that lives within all of your enterprise content

Why your AI isn't working

The average enterprise juggles more than 10 different information management platforms and nearly 1,000 different applications, with a mere 34% of organizations providing an integrated user experience across their channels. This chaos of unstructured data — which constitutes 80-90% of all enterprise information — is scattered across disconnected systems, holding organizations back from fully informed decisions and true innovation. Gartner found 47% of workers struggle to find information or data needed to effectively do their job, and 32% self-reported they’d made a wrong decision due to lack of awareness. These costly inefficiencies stifle progress and pose a massive challenge for the potential impact of AI.

Scattered, sprawling and unstructured data

Many organizations are eager to embrace AI, but their enthusiasm is often met with disappointing results. The problem is deep within their digital infrastructure. The vast majority of enterprise data is unstructured, scattered across a sprawling landscape of disconnected systems and repositories. This disorganization means that employees waste time chasing down the information they need to do their jobs, leading to slow decision-making, increased compliance risks and squandered resources.

> Learn more | Navigating the pros and cons of unstructured data

Most gen AI systems aren’t learning

One core barrier to integrated AI pilots failing is that most gen AI systems aren’t retaining feedback, adapting to context or improving over time. The challenge is compounded by the classic build-vs.-buy argument. Whether due to costs or other objections to working with vendors, many enterprises elect to craft their own solutions — a daunting task in the face of the new and ever-evolving world of effective AI. MIT found that external partnerships were twice as likely to capture success over internal builds. Together, the lack of meaningful impact in the AI pilot leads to lower adoption, largely based on technology that wasn’t able to deliver on the full promise of gen AI.

Legacy systems don’t meet modern AI demands

Fragmentation also creates a significant roadblock for AI adoption. Legacy systems and siloed content repositories were never designed for the demands of modern AI. They lack the necessary structure, governance and accessibility to feed intelligent algorithms. This creates an AI-readiness gap, where organizations have the ambition for AI-driven automation but lack the foundational architecture to execute it successfully. Without a way to unify and make sense of this data, AI initiatives are destined to remain stuck in pilot mode, unable to scale or deliver the meaningful business value that’s expected.

> Learn more | Switching to Hyland

“Your content is more fragmented than it's ever been,” said Hyland CEO Jitesh S. Ghai at our latest annual user event.

The impact is far-reaching and can be life-altering. Healthcare organizations, for example, may be held back by limited insights that can impact care quality and reduce patient volume. Other examples include:

• Admissions and financial aid delays at education institutions

• Slow claims and underwriting at insurance companies

• Delayed responses and a lack of information to lead to the best decisions at public agencies

• Bottlenecks, poor customer experiences and compliance issues in the financial sector

• Logistics inefficiencies, costs and rigidity in commercial businesses

But, Ghai said, what if: Despite all this fragmentation, your enterprise was built on a foundation set for ubiquitous intelligence and automation?

That is, essentially, what Hyland has built. A platform that unifies your enterprise content and data and activates the context within it, making your information AI-ready, insightful, and actionable.

The Content Innovation Cloud is the platform for overcoming these challenges. It provides a federated, AI-powered architecture designed to deliver ubiquitous intelligence and automation across the entire enterprise. The Content Innovation Cloud connects content wherever it lives — across both Hyland and non-Hyland repositories — to make data AI-ready without costly or disruptive migrations. It addresses the core problem of system sprawl head-on and provides a unified view of information that serves as the foundation for intelligent automation and enterprise knowledge.

“We're taking the hundreds of millions of artifacts across your content and data landscape — across your processes — across your fragmented application landscape — and we're connecting it to give you a contextual, complete, real time understanding of your entire enterprise and its operations,” Ghai said.

This helps you connect the people responsible for decision-making to make the best decisions based on the best, most updated data.

At its core, the Content Innovation Cloud is about empowerment, not replacement.

With tools/capabilities like intelligent document processing (IDP) and process automation, it is engineered to deliver solutions that automate mundane, repetitive tasks, thereby freeing human teams to focus on high-value work like strategic problem-solving, creative innovation and critical thinking. By handling the routine approvals, reconciliations and information searches, these products restore power to your people, so they can be more human and drive the business forward.

> Read More | How AI decision-making transforms enterprise operations

The future of ECM

Our vision for the future of ECM is built on a trusted foundation and a commitment to solve the most complex content challenges. The Content Innovation Cloud is the cornerstone of this commitment, offering a stable and expert-driven path into the next era of enterprise AI.

Now, Hyland introduces a new layer to content innovation and intelligence — a radical expansion that will empower an agentic enterprise.

At its core, the Content Innovation Cloud is powered by two industry-first innovations: Hyland Enterprise Context Engine and Hyland Enterprise Agent Mesh.

Together, they bring us to the era of ubiquitous enterprise intelligence and enterprise automation. Both work in concert to bring the agentic enterprise to life.

Enterprise Context Engine

The Enterprise Context Engine acts as the living record of enterprise activity. It is an agentic process that mines years of records, data and decisions to unify content, processes, applications and people. By doing so, it creates a real-time contextual view that makes unstructured information AI-ready. This engine is the mechanism that transforms disorganized, siloed data into a governed, structured asset that can fuel intelligent automation and advanced analytics.

What does it do?

The Enterprise Context Engine, essentially, builds the cognitive core for your enterprise, transforming fragmented information into the intelligence that drives AI-powered outcomes.

Enterprise Agent Mesh

Building on the contextual foundation of the Enterprise Context Engine is Enterprise Agent Mesh, a network of semiautonomous, goal-directed AI agents.

These agents are not generic bots; they can be tailored for specific industries, such as healthcare, insurance, banking or government. They are designed to orchestrate complex workflows, expand institutional knowledge and learn continuously from their interactions.

What does it do?

Agents in the Enterprise Agent Mesh can act alone to handle specific tasks or work together as part of larger agentic solutions that drive impact across departments. They represent a significant leap beyond simple automation, capable of reasoning with governed context to achieve complex goals defined in plain language.

The combination of the Enterprise Context Engine and the Agent Mesh enables what are known as agentic workflows. These are not simple, linear automations but dynamic, goal-directed processes that can reason, adapt and execute complex tasks. They bring a new level of intelligence and efficiency to core business functions.

Here are a few real-world examples of enterprise AI in action:

Customer service

AI-powered chatbots and virtual assistants can handle increasingly complex customer queries, tapping into unified enterprise context to provide accurate and personalized responses, dramatically improving the customer experience.

Human resources

In HR, AI agents can streamline the entire recruitment lifecycle by intelligently matching candidates to open roles. They can also personalize employee onboarding and training programs, leading to higher retention and engagement.

Supply chain management

Predictive AI can analyze historical sales data, market trends and logistical information to forecast demand with incredible accuracy, helping organizations optimize inventory and reduce waste.

Marketing

AI can deliver hyperpersonalized content and offers to customers by integrating with platforms like Salesforce and Workday. It can analyze campaign performance in real time to optimize ad spend and maximize ROI.

“We all collectively have an opportunity in this era of agentic AI to really level up and take the reins,” Ghai said. “They say you can embrace AI and intelligence and shape your organization, or let AI and intelligence shape you.”

Adopting this transformative technology does not require a risky overhaul of your existing systems. The Content Innovation Cloud is designed for a start-today, scale-over-time approach. Each step is designed to build on the last and deliver measurable value along the way. 

Build an AI-ready foundation 

The road to AI-readiness begins by connecting your disparate systems. Content Innovation Cloud’s federated architecture, which doesn’t require migrations, provides a single source of truth by integrating with Hyland repositories, non-Hyland systems and major enterprise applications like Salesforce and Workday. This immediately reduces information silos and improves data governance.

How to achieve it: AI-powered solutions like Hyland IDP and Hyland Knowledge Enrichment process unstructured data; enrich it with context, metadata and ontologies; apply governance and security; and pass it along to your downstream AI solutions, giving you the full power of your organizational knowledge.

Reveal deeper insights

Once your content and intelligence are unified and AI-ready, hidden insights can be revealed that help drive smarter, faster decisions.

How to achieve it: Our Knowledge Enrichment solution works with Hyland Knowledge Discovery to structure all your enterprise content — whether it’s structured or unstructured in its original formatting — and ready it for AI model consumption. With that foundation, Knowledge Discovery enables a consolidated knowledge view and can deliver intelligent search, recommendations and contextual answers, plus the ability to provide domain-aware insights for your specific industry (consider healthcare, insurance, finance, etc.).

Power agentic action

Unified intelligence combined with accelerated automation using Enterprise Agents translates directly into tangible business outcomes. Scale your workforce responsibly by building and deploying a network for tailored AI agents that work as humans do, but with rules in place, humans in the loop and without time constraints. Organizations can expect to see faster decision-making, stronger compliance, reduced operational costs and, most importantly, freed-up human capital to focus on strategic growth and innovation.

How to achieve it: Leveraging the Enterprise Agent Mesh, you can build industry-specific Enterprise Agents to handle document identification and other routine tasks, as well as create a full audit trail for compliance and transparency.

> Read more | Understanding the different types of AI agents

The narrative of enterprise AI is shifting.

The technology is now available to move your enterprise away from a world of fragmented data and failed pilots and toward the reality of a connected, agentic enterprise where humans and AI collaborate to unlock innovation and deliver meaningful outcomes. The key to this transformation is not generating more data, but using the data you already have in smarter, more connected ways.

The future of your enterprise is one where intelligence is seamlessly woven into every interaction, empowering your people by automating the mundane and elevating their work, and by enabling them to work more efficiently and with better informed decisions. This is how everyday tasks are transformed into extraordinary impact. The path to this brighter, more intelligent future is clear.

Discover how the Content Innovation Cloud can help you unify intelligence, accelerate automation, and unlock meaningful results. Contact us to start your journey.